SoroushVahidi/scidocs huggingface dataset:
Real-time categorization of driver's gaze zone using the deep learning techniques
(2016)

This paper presents a study in which driver's gaze zone is categorized using new deep learning techniques. Since the sequence of gaze zones of a driver reflects precisely what and how he behaves, it allows us infer his drowsiness, focusing or distraction by analyzing the images coming from a camera. A Haar feature based face detector is combined with a correlation filter based MOSS tracker for the face detection task to handle a tough visual environment in the car. Driving database is a big-data which was constructed using a recording setup within a compact sedan by driving around the urban area. The gaze zones consist of 9 categories depending on where a driver is looking at during driving. A convolutional neural network is trained to categorize driver's gaze zone from a given face detected image using a multi-GPU platform, and then its network parameters are transferred to a GPU within a PC running on Windows to operate in the real-time basis. Result suggests that the correct rate of gaze zone categorization reaches to 95% in average, indicating that our system outperforms the state-of-art gaze zone categorization methods based on conventional computer vision techniques.
New Branch Prediction Vulnerabilities in OpenSSL and Necessary Software Countermeasures
(2007)

Software based side-channel attacks allow an unprivileged spy process to extract secret information from a victim (cryptosystem) process by exploiting some indirect leakage of “side-channel” information. It has been realized that some components of modern computer microarchitectures leak certain side-channel information and can create unforeseen security risks. An example of such MicroArchitectural Side-Channel Analysis is the Cache Attack — a group of attacks that exploit information leaks from cache latencies [4, 7, 13, 15, 17]. Public awareness of Cache Attack vulnerabilities lead software writers of OpenSSL (version 0.9.8a and subsequent versions) to incorporate countermeasures for preventing these attacks. In this paper, we present a new and yet unforeseen side channel attack that is enabled by the recently published Simple Branch Prediction Analysis (SBPA) which is another type of MicroArchitectural Analysis, cf. [2, 3]. We show that modular inversion — a critical primitive in public key cryptography — is a natural target of SBPA attacks because it typically uses the Binary Extended Euclidean algorithm whose nature is an input-centric sequence of conditional branches. Our results show that SBPA can be used to extract secret parameters during the execution of the Binary Extended Euclidean algorithm. This poses a new potential risk to crypto-applications such as OpenSSL, which already employs Cache Attack countermeasures. Thus, it is necessary to develop new software mitigation techniques for BPA and incorporate them with cache analysis countermeasures in security applications. To mitigate this new risk in full generality, we apply a security-aware algorithm design methodology and propose some changes to the CRT-RSA algorithm flow. These changes either avoid some of the steps that require modular inversion, or remove the critical information leak from this procedure. In addition, we also show by example that, independently of the required changes in the algorithms, careful software analysis is also required in order to assure that the software implementation does not inadvertently introduce branches that may expose the application to SBPA attacks. These offer several simple ways for modifying OpenSSL in order to mitigate Branch Prediction Attacks.
Omnidirectional planar dipole array antenna for WLAN access point
(2003)

In this paper, a low-cost planar dipole array antenna with an omnidirectional radiation characteristic is presented. The proposed omnidirectional planar dipole array antenna comprises two 1/spl times/2 dipole arrays arranged back to back, and can be easily constructed by printing on both sides of a dielectric substrate. By selecting the central ground plane to have a small width (about 6 mm for operating at about 2.4 GHz), the proposed array antenna can have a good omnidirectional radiation pattern in the azimuthal plane (gain variations less than 2 dBi). Prototypes of the proposed antenna for WLAN operation in the 2.4 GHz band (2400-2484 MHz) were constructed and studied.
An ear-worn continuous ballistocardiogram (BCG) sensor for cardiovascular monitoring
(2012)

Traditionally, ballistocardiogram (BCG) has been measured using large and stationary devices. In this work, we demonstrate a portable and continuous BCG monitor that is wearable at the ear. The device has the form factor of a hearing aid and is wirelessly connected to a PC for data recording and analysis. With the ear as an anchoring point, the device uses a MEMS tri-axial accelerometer to measure BCG at the head. Morphological differences exist between head BCG and traditional BCG, but the principal peaks (J waves) and their vectors are preserved. The frequency of J waves corresponds to heart rate, and when used in conjunction with an electrocardiogram's (ECG) R wave, the timing of J waves yields the RJ interval. Results from our clinical study show linear correlation between the RJ interval and the heart's pre-ejection period during hemodynamic maneuvers, thus revealing important information about cardiac contractility and its regulation.
SimICS/Sun4m: A Virtual Workstation
(1998)

System level simulators allow computer architects and system software designers to recreate an accurate and complete replica of the program behavior of a target system, regardless of the availability, existence, or instrumentation support of such a system. Applications include evaluation of architectural design alternatives as well as software engineering tasks such as traditional debugging and performance tuning. We present an implementation of a simulator acting as a virtual workstation fully compatible with the sun4m architecture from Sun Microsystems. Built using the system-level SPARC V8 simulator SimICS, SimICS/sun4m models one or more SPARC V8 processors, supports user-developed modules for data cache and instruction cache simulation and execution profiling of all code, and provides a symbolic and performance debugging environment for operating systems. SimICS/sun4m can boot unmodified operating systems, including Linux 2.0.30 and Solaris 2.6, directly from snapshots of disk partitions. To support essentially arbitrary code, we implemented binary-compatible simulators for several devices, including SCSI, console, interrupt, timers, EEPROM, and Ethernet. The Ethernet simulation hooks into the host and allows the virtual workstation to appear on the local network with full services available ( NFS, NIS, rsh, etc). Ethernet and console traffic can be recorded for future playback. The performance of SimICS/sun4m is sufficient to run realistic workloads, such as the database benchmark TPC-D, scaling factor 1/100, or an interactive network application such as Mozilla. The slowdown in relation to native hardware is in the range of 25 to 75 (measured using SPECint95). We also demonstrate some applications, including modeling an 8-processor sun4m version (which does not exist), modeling future memory hierarchies, and debugging an operating system.
A pattern recognition approach to voiced-unvoiced-silence classification with applications to speech recognition
(1976)

Absb-act—In speech analysis, the voiced-unvoiced decision is usually performed in conjunction with pitch analysis. The linking of voiced-unvoiced (V-UV) decision to pitch analysis not only results in unnecessary complexity, but makes it difficult to classify short speech segments which are less than a few pitch periods in duration. In this paper, we describe a pattern recognition approach for deciding whether a given segment of a speech signal should be classified as voiced speech, un-voiced speech, or silence, based on measurements made on the signal. In this method, five different measurements axe made on the speech segment to be classified. The measured parameters are the zero-crossing rate, the speech energy, the correlation between adjacent speech samples, the first predictor coefficient from a 12-pole linear predictive coding (LPC) analysis, and the energy in the prediction error. The speech segment is assigned to a particular class based on a minimum-distance rule obtained under the assumption that the measured parameters are distributed according to the multidimensional Gaussian probability density function. The means and covariances for the Gaussian distribution are determined from manually classified speech data included in a training set. The method has been found to provide reliable classification with speech segments as short as 10 ms and has been used for both speech analysis-synthesis and recognition applications. A simple nonlinear smoothing algorithm is described to provide a smooth 3-level contour of an utterance for use in speech recognition applications. Quantitative results and several examples illustrating the performance of the methOd are included in the paper.
Feudal Multi-Agent Hierarchies for Cooperative Reinforcement Learning
(2019)

We investigate how reinforcement learning agents can learn to cooperate. Drawing inspiration from human societies, in which successful coordination of many individuals is often facilitated by hierarchical organisation, we introduce Feudal Multiagent Hierarchies (FMH). In this framework, a ‘manager’ agent, which is tasked with maximising the environmentally-determined reward function, learns to communicate subgoals to multiple, simultaneously-operating, ‘worker’ agents. Workers, which are rewarded for achieving managerial subgoals, take concurrent actions in the world. We outline the structure of FMH and demonstrate its potential for decentralised learning and control. We find that, given an adequate set of subgoals from which to choose, FMH performs, and particularly scales, substantially better than cooperative approaches that use a shared reward function.
Feature Selection with Linked Data in Social Media
(2012)

Feature selection is widely used in preparing highdimensional data for effective data mining. Increasingly popular social media data presents new challenges to feature selection. Social media data consists of (1) traditional high-dimensional, attribute-value data such as posts, tweets, comments, and images, and (2) linked data that describes the relationships between social media users as well as who post the posts, etc. The nature of social media also determines that its data is massive, noisy, and incomplete, which exacerbates the already challenging problem of feature selection. In this paper, we illustrate the differences between attributevalue data and social media data, investigate if linked data can be exploited in a new feature selection framework by taking advantage of social science theories, extensively evaluate the effects of user-user and user-post relationships manifested in linked data on feature selection, and discuss some research issues for future work.
River flow estimation using adaptive neuro fuzzy inference system
(2007)

Accurate estimation of River flow changes is a quite important problem for a wise and sustainable use. Such a problem is crucial to the works and decisions related to the water resources and management. In this study, an adaptive network-based fuzzy inference system (ANFIS) approach was used to construct a River flow forecasting system. In particular, the applicability of ANFIS as an estimation model for River flow was investigated. To illustrate the applicability and capability of the ANFIS, the River Great Menderes, located the west of Turkey and the most important water resource of Great Menderes Catchment’s, was chosen as a case study area. The advantage of this method is that it uses the input–output data sets. Totally 5844 daily data sets collected in 1985–2000 years were used to estimate the River flow. The models having various input structures were constructed and the best structure was investigated. In addition four various training/testing data sets were constructed by cross validation methods and the best data set was investigated. The performance of the ANFIS models in training and testing sets were compared with the observations and also evaluated. The results indicated that the ANFIS can be applied successfully and provide high accuracy and reliability for River flow estimation. © 2006 IMACS. Published by Elsevier B.V. All rights reserved.
CASIA@V2: A MLN-based Question Answering System over Linked Data
(2014)

We present a question answering system (CASIA@V2) over Linked Data (DBpedia), which translates natural language questions into structured queries automatically. Existing systems usually adopt a pipeline framework, which contains four major steps: 1) Decomposing the question and detecting candidate phrases; 2) mapping the detected phrases into semantic items of Linked Data; 3) grouping the mapped semantic items into semantic triples; and 4) generating the rightful SPARQL query. We present a jointly learning framework using Markov Logic Network(MLN) for phrase detection, phrases mapping to semantic items and semantic items grouping. We formulate the knowledge for resolving the ambiguities in three steps of QALD as first-order logic clauses in a MLN. We evaluate our approach on QALD-4 test dataset and achieve an F-measure score of 0.36, an average precision of 0.32 and an average recall of 0.40 over 50 questions.
Offset Reduction of CMOS Based DynamicComparator by using Charge Storage Techniques- A Comparative Study
(2013)

Comparator is one of the most widely used building block for analog and mixed signal systems. For the implementation of high-performance CMOS A/D converters, low offset comparators are essential. In this paper, dynamic comparator offset is calculated to the extent of high accuracy. The offset so calculated has been reduced by the charge storage techniques to achieve an efficient design. In addition to the offset, propagation delay and power dissipation, being the important parameter of the comparator, has been analyzed. It is observed that offset voltage in the comparator has been reduced to 350μV for output offset storage technique and 400μV for input offset storage techniques from 91mV. In this paper, BPTM model has been used in analyze the dynamic comparator. KeywordsDynamic comparator, offset voltage, storage capacitor, input offset storage, output offset storage.
Super-resolution through neighbor embedding
(2004)

In this paper, we propose a novel method for solving single-image super-resolution problems. Given a low-resolution image as input, we recover its high-resolution counterpart using a set of training examples. While this formulation resembles other learning-based methods for super-resolution, our method has been inspired by recent manifold teaming methods, particularly locally linear embedding (LLE). Specifically, small image patches in the lowand high-resolution images form manifolds with similar local geometry in two distinct feature spaces. As in LLE, local geometry is characterized by how a feature vector corresponding to a patch can be reconstructed by its neighbors in the feature space. Besides using the training image pairs to estimate the high-resolution embedding, we also enforce local compatibility and smoothness constraints between patches in the target high-resolution image through overlapping. Experiments show that our method is very flexible and gives good empirical results.
Example-Based Super-Resolution
(2002)

Image-based models for computer graphics lack resolution independence: they cannot be zoomed much beyond the pixel resolution they were sampled at without a degradation of quality. Interpolating images usually results in a blurring of edges and image details. We describe image interpolation algorithms which use a database of training images to create plausible high-frequency details in zoomed images. Image pre-processing steps allow the use of image detail from regions of the training images which may look quite di erent from the image to be processed. These methods preserve ne details, such as edges, generate believable textures, and can give good results even after zooming multiple octaves. This work may not be copied or reproduced in whole or in part for any commercial purpose. Permission to copy in whole or in part without payment of fee is granted for nonpro t educational and research purposes provided that all such whole or partial copies include the following: a notice that such copying is by permission of Mitsubishi Electric Information Technology Center America; an acknowledgment of the authors and individual contributions to the work; and all applicable portions of the copyright notice. Copying, reproduction, or republishing for any other purpose shall require a license with payment of fee to Mitsubishi Electric Information Technology Center America. All rights reserved. Copyright c Mitsubishi Electric Information Technology Center America, 2001 201 Broadway, Cambridge, Massachusetts 02139 1. First printing, TR2001-30, August, 2001. Egon Pasztor's present address: MIT Media Lab 20 Ames St. Cambridge, MA 02139 Example-based Super-resolution William T. Freeman, Thouis R. Jones, Egon C. Pasztor MitsubishiElectricResearchLaboratories(MERL) 201Broadway Cambridge,MA 02139 (a) (b) Figure 1: An object modelledby traditionalpolygon techniques may lack someof the richnessof real-world objects,but behaves properlyunderzooming,(b).
Mediating intimacy: designing technologies to support strong-tie relationships
(2005)

Intimacy is a crucial element of domestic life, and many interactive technologies designed for other purposes have been appropriated for use within intimate relationships. However, there is a deficit in current understandings of how technologies are used within intimate relationships, and how to design technologies to support intimate acts. In this paper we report on work that has addressed these deficits. We used cultural probes and contextual interviews and other ethnographically informed techniques to investigate how interactive technologies are used within intimate relationships. From this empirical work we generated a thematic understanding of intimacy and the use of interactional technologies to support intimate acts. We used this understanding to inform the design of intimate technologies. A selection of our design concepts is also presented.
The dynamics of innovation : from National Systems and ‘ ‘ Mode 2 ’ ’ to a Triple Helix of university – industry – government relations
(2000)

The Triple Helix of university–industry–government relations is compared with alternative models for explaining the current research system in its social contexts. Communications and negotiations between institutional partners generate an overlay that increasingly reorganizes the underlying arrangements. The institutional layer can be considered as the retention mechanism of a developing system. For example, the national organization of the system of innovation has historically been important in determining competition. Reorganizations across industrial sectors and nation states, however, are induced by Ž . Ž . new technologies biotechnology, ICT . The consequent transformations can be analyzed in terms of neoevolutionary mechanisms. University research may function increasingly as a locus in the ‘‘laboratory’’ of such knowledge-intensive network transitions. q 2000 Elsevier Science B.V. All rights reserved.
Text and Object Detection on Billboards
(2018)

To captivate people’s attention in a blink of an eye, a billboard as a commercial advertisement must be attractive and informative. When space means money like on the billboard, much important information must be dropped out. Unfortunately, insufficient details and the difficulty of accessing those details might easily kill the customer’s attention in a flash as well. In this work, we propose a system that automatically connects a billboard with the product website instantly. More specifically, given the billboard image as an input, the system will lead users immediately to the product website for more details, or contact information. The results demonstrate that our system is significantly outperform the Google image search baseline where the product website is always included in the top 10 websites. Finally, We posit that the system can save the customers’ time and complexity to access their product of interest, resulting the increasing of product sale.
Lean, six sigma and lean sigma: fads or real process improvement methods?
(2008)

Purpose – The purpose of this paper is to explore if six sigma and lean are new methods, or if they are repackaged versions of previously popular methods – total quality management (TQM) and just-in-time (JIT). Design/methodology/approach – The study is based on a critical comparison of lean with JIT and six sigma with TQM, a study of the measure of the publication frequency – the number of academic articles published every year of the previous 30 years – for each topic, and a review of critical success factors (CSF) for change efforts. Findings – The more recent concepts of lean and six sigma have mainly replaced – but not necessarily added to – the concepts of JIT and TQM. lean and six sigma are essentially repackaged versions of the former, and the methods seem to follow the fad (product) life cycle. The literature offers fairly similar and rather general CSF for these methods, e.g. top management support and the importance of communication and information. What seems to be missing, however, is the need for a systemic approach to organizational change and improvement. Practical implications – A prediction is, given the fad or product life cycle phenomenon, that there will be a new method promoted soon, something perhaps already experienced with the borderline preposterous concept of lean six sigma. On the other hand, based on the gap in time between both JIT and lean, and TQM and six sigma – a gap filled by BRP/reengineering – the next method will be process oriented. This paper concludes with the discussion of the need for a process-based approach to organizational improvement efforts. Originality/value – This paper is of value in that it analyzes what lessons can be learnt from organizational change and improvement efforts. The analysis includes a comparison of CSF for any change project before discussing the need for a process (systems) perspective for successful organizational improvement efforts.